Model vs benchmark — deteksi bias sistematis
Bias rata-rata (mean error %)
0,5
Volatilitas error σ_e (%)
1,2
Autokorelasi error (ρ lag-1)
0,3
Sample size T
250
RMSE
—
akar MSE
MAE
—
mean abs error
Diebold-Mariano
—
vs benchmark
Status
—
model/benchmark
Reset
Error model vs aktual — pola sistematis